FIG. 4 is a block diagram for a vehicle yaw control system in which a driver intervenes, and for example a case in which a driver controls the azimuth of a vehicle by operating a steering wheel so that the vehicle travels along a white line of a road is envisaged. The driver visually recognizes an azimuth deviation, which is a deviation between a target azimuth for making the direction of travel of the vehicle follow the direction of the white line and an actual azimuth that is actually generated in the vehicle, assesses in which direction and by how much the steering wheel is to be operated, and operates the steering wheel. As a result, a steering angle is generated in the steering wheel, the vehicle responds, and a change is generated in the azimuth. In this process, vehicle behavior is influenced by environmental factors such as the coefficient of friction of the road surface and the load of the vehicle, and an actual azimuth is finally generated.
If the driver is falling asleep at the wheel, since it becomes difficult to make the vehicle travel along the white line of the road with good precision, the azimuth deviation increases. It is therefore possible by observing the azimuth deviation to assess that the driver is in a low wakefulness state. However, this method is based on control results (white line tracking precision) from driving performance, and since a low wakefulness state is assessed based on the driving results manifested in the actual vehicle behavior, there is a possibility that a delay will occur in the assessment.
If a driver model, in which a driver is modeled, is identified and a comparison is made between the output (driver model steering angle) when an azimuth deviation is inputted thereinto and the actual driver's output (actual steering angle), a driver's low wakefulness state can be assessed without waiting for a change in the vehicle behavior, and it becomes possible to carry out assessment at an earlier stage.
As a driver state assessment device employing such a driver model, an arrangement in which evaluation of a current driver's state (falling asleep at the wheel or driving under the influence of alcohol) is carried out by identifying a driver model based on outputs from a vehicle-installed target value sensor (lane detecting camera), a movement sensor (yaw rate sensor), and an operation sensor (steering angle sensor) and comparing this driver model with a standard driver model is known from Patent Document 1 below.